The quantum cognition approach draws upon a mathematical framework originally developed for quantum mechanics. One phenomenon that is particularly well captured by quantum models but not classical ones, known as the Question Order Effect, is that the order of questions can alter the answers given. This paper describes at a layperson level a study that uses this effect to ascertain whether creative thinking and the processing of unfamiliar stimuli both elicit cognitive states and processes that are best described by a quantum model. The rationale is that both involve key quantum features that the quantum formalism is particularly well-suited to capture: ambiguity and contextuality.
The quantum cognition approach draws upon a mathematical framework originally developed for quantum mechanics. One phenomenon that is particularly well captured by quantum models but not classical ones, known as the Question Order Effect, is that the order of questions can alter the answers given. This paper describes at a layperson level a study that uses this effect to ascertain whether creative thinking and the processing of unfamiliar stimuli both elicit cognitive states and processes that are best described by a quantum model. The rationale is that both involve key quantum features that the quantum formalism is particularly well-suited to capture: ambiguity and contextuality.
Classical models of decision-making under uncertainty, grounded in expected utility theory and Bayesian probability, often fail to account for systematic cognitive anomalies such as preference reversals, order effects, ambiguity aversion, and context-dependent choices. Quantum cognition models offer a novel theoretical framework that applies the mathematical principles of quantum probability—such as superposition, interference, and non-commutativity—to cognitive processes without assuming physical quantum mechanisms in the brain. By representing cognitive states as probabilistic superpositions that collapse through decision “measurements,” these models provide parsimonious explanations for violations of classical rationality. This paper examines how quantum cognition frameworks capture contextual influence, belief updating, and interference effects in uncertain decision environments. Drawing on findings from cognitive psychology and behavioral economics, the study highlights the relevance of quantum cognition for applications in economic choice modeling, legal decision analysis, and artificial intelligence. The analysis suggests that quantum probability offers a robust alternative to classical approaches when modeling human decision-making in complex, ambiguous, and context-sensitive situations.
Is mind quantum-like? Is consciousness quantum physical? Does consciousness have a role to play in the emergence of the classical world from the underlying quantum universe? Or is this dichotomy between classical and quantum an illusion? How can world philosophies enrich our views on these matters and interact with the best scientific theories? These are some questions that motivated us to conceive the current book. We also felt an urgent need to discuss the central philosophical questions haunting the emerging frameworks of quantum cognition and quantum-like framework (QLF). We have observed that there are very good technical or mathematical works being done in the emerging fields of quantum cognition and QLF, but there is still a great need for exploring the underlying and open philosophical questions they demand. Quantum cognition developed as a frontier research programme in understanding various cognitive phenomena that are hard or impossible to describe based on classical cognitive science paradigm. Classical cognitive science draws philosophically and mathematically from classical physics and classical probability theory. For example, cognitive realism thinking is deeply motivated by the scientific realism of classical physics. However, as we explore, there are numerous empirical findings which demonstrate clearly that human mind and cognitive processes exhibit features that are more quantum-like. Central to these features are indeterminacy, context dependence, and complementarity of cognitive phenomena, for example, perception, information retrieval, and even qualia. Many good works in the previous decade have demonstrated the efficacy of quantum-like mathematical modelling in such cases. However, given that efficacy, we cannot simply conclude that mind is quantum. Rather there are features that go beyond what is allowed in standard quantum formalism.
The mathematical formalism of quantum mechanics has been successfully employed in the last years to model situations in which the use of classical structures gives rise to problematical situations, and where typically quantum effects, such as 'contextuality' and 'entanglement', have been recognized. This 'Quantum Interaction Approach' is briefly reviewed in this paper focusing, in particular, on the quantum models that have been elaborated to describe how concepts combine in cognitive science, and on the ensuing identification of a quantum structure in human thought. We point out that these results provide interesting insights toward the development of a unified theory for meaning and knowledge formalization and representation. Then, we analyze the technological aspects and implications of our approach, and a particular attention is devoted to the connections with symbolic artificial intelligence, quantum computation and robotics.
Experiments in cognitive science and decision theory show that the ways in which people combine concepts and make decisions cannot be described by classical logic and probability theory. This has serious implications for applied disciplines such as information retrieval, artificial intelligence and robotics. Inspired by a mathematical formalism that generalizes quantum mechanics the authors have constructed a contextual framework for both concept representation and decision making, together with quantum models that are in strong alignment with experimental data. The results can be interpreted by assuming the existence in human thought of a double-layered structure, a 'classical logical thought' and a 'quantum conceptual thought', the latter being responsible of the above paradoxes and nonclassical effects. The presence of a quantum structure in cognition is relevant, for it shows that quantum mechanics provides not only a useful modeling tool for experimental data but also supplies a structural model for human and artificial thought processes. This approach has strong connections with theories formalizing meaning, such as semantic analysis, and has also a deep impact on computer science, information retrieval and artificial intelligence. More specifically, the links with information retrieval are discussed in this paper.
At the heart of creativity is the forging of new concept combinations and the adapting of existing ideas to new situations. However, these processes have resisted mathematical description; concepts violate the rules of classical logic when they interact, e.g., concept combinations can exhibit emergent features not possessed by their constituent concepts. These challenges can be addressed using the quantum cognition framework, wherein nonclassical behavior is described in terms of superposition, entanglement, and interference. While in classical probability theory events are drawn from a common sample space, in quantum models events are defined only with respect to a measurement, or (in quantum cognition) a context, and the probabilities reflect the underlying reality. The measurement (or context) causes collapse from a superposition state to a definite eigenstate. The paper explains how creativity can be modelled using quantum cognition approach with an illustrative example, and discuss how the approach could be implemented computationally. Quantum computing is widely expected to revolutionize many fields in the near future through immense increases in speed and computing power. The time may be ripe to explore the potential of quantum computational creativity.
Quantum cognition, a growing topic at the interface of quantum physics and cognitive research, provides a new viewpoint on the intricacies of human thought processes. In contrast to classic Boolean algebraic models, which have long dominated cognitive psychology, quantum cognition proposes a new framework influenced by quantum mechanics' algebraic structure. This deviation derives from the understanding that natural notions, based on prototypes, are more closely related to convex sets than to the rigid rules of Boolean algebra. Drawing on the fundamental work of luminaries such as John von Neumann, quantum cognition reveals a unique probability theory based on ortho-algebras, challenging traditional probabilistic reasoning based on Boolean algebras. This change opens up solutions to complex challenges in rationality, logical thinking, and probabilistic reasoning, ushering in a new era of cognitive modelling. Several arguments in the literature support the importance of quantum cognition in explaining cognitive phenomena.